I am guessing there is a balance between a language that has a lot of soundness checks (like Rust) and a language that has a ton of example code to train on (like Python). How much more valuable each aspect is I am not sure.

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echelon 4 hours ago | parent [-]

Rust is the best language for AI:

- Rust code generates absolutely perfectly in Claude Code.

- Rust code will run without GC. You get that for free.

- Rust code has a low defect rate per LOC, at least measured by humans. Google gave a talk on this. The sum types + match and destructure make error handling ergonomic and more or less required by idiomatic code, which the LLM will generate.

I'd certainly pick Rust or Go over Python or TypeScript. I've had LLMs emit buggy dynamic code with type and parameter mismatches, but almost never statically typed code that fails to compile.

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moritz 4 hours ago | parent | next [-]

https://arxiv.org/abs/2508.09101

In this benchmark, models can correctly solve Rust problems 61% on first pass — A far cry from other languages such as C# (88%) or Elixir (a “buggy dynamic language”) where they perform best (97%).

I wonder why that is, it’s quite surprising. Obviously details of their benchmark design matter, but this study doesn’t support your claims.

	▲	squeegmeister 3 hours ago \| parent [-]
		This is great, but aug 2025 is almost a lifetime ago with how fast these models are improving. Opus 4.5 came out November 2025 fwiw

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xigoi 4 hours ago | parent | prev [-]

The downside is that even simple Rust projects typically use hundreds of dependencies, and this is even worse with LLMs, who don’t understand the concept of “less is more”.

	▲	echelon 3 hours ago \| parent [-]
		Nobody forces dependencies on you. You can control that.